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# Staff AI Data Scientist- Remote

- **Company:** BeyondTrust Corporation
- **Location:** Johns Creek, United States (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cyber Security, Information Engineering, Python (Programming Language), Machine Learning, Open Source Technology, Raw Data, Tensorflow, Software Safety, Software Engineering, GitHub Copilot, Pytorch, Large Language Models, Deep Learning, Scikit Learn, Information Technology, HuggingFace, Machine Learning Operations
- **Published:** May 14, 2026
- **Apply:** https://arc.dev/remote-jobs/j/beyondtrust-staff-ai-data-scientist-remote-opuduiq70u

## About the Role

* Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field (or equivalent practical experience)
 * 3+ years of hands-on experience building and deploying ML models in production environments
 * Strong proficiency in Python and ML frameworks such as PyTorch, TensorFlow, scikit-learn, and Hugging Face Transformers
 * Deep understanding of statistical modeling, experimental design, and evaluation methodology
 * Experience with cloud platforms (AWS, GCP, or Azure) for training, serving, and scaling models
 * Familiarity with LLM fine-tuning techniques (LoRA, RLHF, instruction tuning) and serving infrastructure
 * Experience leveraging AI coding assistants (such as Claude Code, OpenCode, or GitHub Copilot) to accelerate development workflows

Nice To Have

 * Background in cybersecurity, identity security, or anomaly detection
 * Familiarity with adversarial ML or AI safety research
 * Contributions to open-source projects or published research

## Description

We're looking for a Staff AI Data Scientist to design, build, and deploy machine learning models and AI-driven solutions that solve complex business problems. You'll work at the intersection of applied research, software engineering, and product - turning raw data into actionable insights and intelligent systems that ship to production.

What You'll Do

 * Develop and deploy machine learning models (supervised, unsupervised, deep learning) for production use cases
 * Design experiments, define success metrics, and run rigorous offline and online evaluations (A/B tests, holdouts, causal analyses)
 * Fine-tune, prompt-engineer, and evaluate large language models for domain-specific tasks
 * Partner with data engineering to define the features, datasets, and pipelines needed for model training and inference
 * Collaborate with engineering, product, and business teams to translate ambiguous problems into well-scoped modeling solutions
 * Build monitoring and evaluation frameworks to track model performance, drift, and fairness over time
 * Communicate findings and recommendations to both technical and non-technical stakeholders through clear visualizations and written reports
 * Mentor other data scientists and help raise the bar for modeling rigor across the team


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